Background: What and how teachers learn through teaching without external guidance has long been of interest to researchers. Yet limited research has been conducted to investigate how learning through teaching occurs. The microgenetic approach (Siegler and Crowley, American Psychologist 46:606–620, 1991) has been useful in identifying the process of student learning. Using this approach, we investigated the development of teacher knowledge through teaching as well as which factors hinder or promote such development. Results: Our findings suggest that teachers developed various components of teacher knowledge through teaching without external professional guidance. Further, we found that the extent to which teachers gained content-free or content-specific knowledge through teaching depended on their robust understanding of the concept being taught (i.e., content knowledge), the cognitive demand of the tasks used in teaching, and the lesson structure chosen (i.e., student centered vs. teacher centered). Conclusions: In this study, we explored teacher learning through teaching and identified the sources leading to such learning. Our findings underscore the importance of teachers’ robust understanding of the content being taught, the tasks used in teaching, and a lesson structure that promotes teachers’ learning through teaching on their own. © The Author(s) 2024.

Background: Studying science identity has been useful for understanding students' continuation in science-related education and career paths. Yet knowledge and theory related to science identity among students on the path to becoming a professional science researcher, such as students engaged in research at the undergraduate, postbaccalaureate, and graduate level, is still developing. It is not yet clear from existing science identity theory how particular science contexts, such as research training experiences, influence students' science identities. Here we leverage existing science identity and professional identity theories to investigate how research training shapes science identity. We conducted a qualitative investigation of 30 early career researchers--undergraduates, postbaccalaureates, and doctoral students in a variety of natural science fields--to characterize how they recognized themselves as science researchers. Results: Early career researchers (ECRs) recognized themselves as either science students or science researchers, which they distinguished from being a career researcher. ECRs made judgments, which we refer to as "science identity assessments", in the context of interconnected work-learning and identity-learning cycles. Work-learning cycles referred to ECRs' conceptions of the work they did in their research training experience. ECRs weighed the extent to which they perceived the work they did in their research training to show authenticity, offer room for autonomy, and afford opportunities for epistemic involvement. Identity-learning cycles encompassed ECRs' conceptions of science researchers. ECRs considered the roles they fill in their research training experiences and if these roles aligned with their perceptions of the tasks and traits of perceived researchers. ECRs' identity-learning cycles were further shaped by recognition from others. ECRs spoke of how recognition from others embedded within their research training experiences and from others removed from their research training experiences influenced how they see themselves as science researchers. Conclusions: We synthesized our findings to form a revised conceptual model of science researcher identity, which offers enhanced theoretical precision to study science identity in the future. We hypothesize relationships among constructs related to science identity and professional identity development that can be tested in further research. Our results also offer practical implications to foster the science researcher identity of ECRs.

Amid the proliferation of state-level bans on race-based affirmative action in higher education, the U.S. Supreme Court's decision on June 29, 2023, dismantled race-conscious college admission policies, intensifying concerns about the persistence and potential increase of racial inequality in higher education. The authors analyze four restricted-use national survey datasets to investigate racial disparities in college attendance outcomes from the 1980s through the 2010s. Although college entrance rates increased for all racial groups, Black and Hispanic youth became increasingly less likely than their White peers to attend four-year selective colleges. In the 2010s cohort, Black and Hispanic youth were 8 and 7 percentage points, respectively, less likely than their White counterparts to secure admission to four-year selective colleges, even after controlling for parents' income, education, and other family background variables. The findings underscore the urgent need for proactive policy interventions to address the widening racial inequality in attending selective postsecondary institutions.

Collaboration is key to STEM, where multidisciplinary team research can solve complex problems. However, inequality in STEM fields hinders their full potential, due to persistent psychological barriers in underrepresented students’ experience. This paper documents teamwork in STEM and explores the transformative potential of computational modeling and generative AI in promoting STEM-team diversity and inclusion. Leveraging generative AI, this paper outlines two primary areas for advancing diversity, equity, and inclusion. First, formalizing collaboration assessment with inclusive analytics can capture fine-grained learner behavior. Second, adaptive, personalized AI systems can support diversity and inclusion in STEM teams. Four policy recommendations highlight AI's capacity: formalized collaborative skill assessment, inclusive analytics, funding for socio-cognitive research, human-AI teaming for inclusion training. Researchers, educators, and policymakers can build an equitable STEM ecosystem. This roadmap advances AI-enhanced collaboration, offering a vision for the future of STEM where diverse voices are actively encouraged and heard within collaborative scientific endeavors. © The Author(s) 2024.

Cognitive science of learning points to solutions for making use of existing study and instruction time more effectively and efficiently. However, solutions are not and cannot be one-size-fits-all. This paper outlines the danger of overreliance on specific strategies as one-size-fits-all recommendations and highlights instead the cognitive learning processes that facilitate meaningful and long-lasting learning. Three of the most commonly recommended strategies from cognitive science provide a starting point; understanding the underlying processes allows us to tailor these recommendations to implement at the right time, in the right way, for the right content, and for the right students. Recommendations regard teacher training, the funding and incentivizing of educational interventions, guidelines for the development of educational technologies, and policies that focus on using existing instructional time more wisely. © The Author(s) 2023.

Collaborations between education stakeholders are increasingly prevalent due to the need for diverse perspectives on issues of justice in education. Less is known, however, about how stakeholders form heterogeneous communities where people from different backgrounds learn and take action together. This study examined the contours of a community that emerged from a three-year partnership between mathematics teachers, community educators, and university scholars. This racially- and gender-diverse community was marked by contention and affirmation, which illuminates the complex and politicized nature of the joint work. This study illuminates tensions across dimensions of the community including spaces as affirming and fraught, goals as shared and contested, belonging as ebbing and flowing, relationships as personal and political, and roles as imposed and amorphous.

The current study aimed to 1) identify patterns of ethnic-racial and coping socialization among Black emerging adults, and 2) investigate profile differences in demographics and family relationship quality (e.g., communication and closeness). Six-hundred and three Black emerging adults (Mage = 18.63, 78% Female) at a Minority Serving Institution completed an online survey. We used latent profile analysis (LPA) with three ethnic-racial socialization and two coping socialization indicators. Four profiles emerged: High Socialization, Awareness without Response, Colorblind Coping, and Low Socialization. African American emerging adults were more likely to be in the High Socialization group than other profiles. Those in the High Socialization profile (high ethnic-racial socialization and racial coping socialization) were likely to report parental closeness more than others. Differences in family communication are discussed. The findings reveal that coping support and race-related socialization messages matter throughout emerging adulthood.

Though many studies suggest the positive effects of leaderboard on participants’ learning and motivation, research also shows that not all students benefit from the use of leaderboard. Based on self-determination theory (SDT), this study examined how students’ actual competence, perceived competence, perceived autonomy, and perceived relatedness affected students’ enjoyment and intention for future participation in a leaderboard-based math practice game. The results showed that both perceived competence and perceived autonomy were closely related to students’ enjoyment and intention for future participation, while students’ actual competence and perceived relatedness were not related to their enjoyment or intention for future participation in such leaderboard-based math practice games. The findings of the study offer valuable insights and recommendations for both gamification research and practice.

A robust left digit effect arises in number line estimation, whereby the leftmost digits of numerals have an undue influence on placements such that, for example, numbers like 298 are placed far to the left of numbers like 302. Past efforts to motivate more accurate performance using trial-by-trial and summary feedback have not led to a reduction in the left digit effect. In two experiments, we asked whether it is possible to reduce or eliminate the left digit effect in number line estimation through an instructional intervention in which one is explicitly taught about the left digit effect. In Experiment 1 (N = 134), participants completed two blocks (60 trials per block) of a self-paced 0-1,000 number line estimation task and were randomly assigned to either an instruction or a control condition. In Experiment 2 (N = 143), the procedure was enhanced with a learning check, and with additional measures to assess changes in behaviour as a result of instruction. In both experiments, a left digit effect was found in each block of each condition. Although there was evidence that instruction changed behaviour, these changes did not result in any reduction in the left digit effect relative to the control condition. These findings demonstrate that the left digit effect cannot be easily reduced by making people aware of it.

Meta-analytic evidence indicates that the quality of the attachment relationship that infants establish with their primary caregiver has enduring significance for socioemotional and cognitive outcomes. However, the mechanisms by which early attachment experiences contribute to subsequent development remain underspecified. According to attachment theory, early attachment experiences become embodied in the form of cognitive-affective representations, referred to as internal working models (IWMs), that guide future behavior. Little is known, however, about the cognitive architecture of IWMs in infancy. In this article, we discuss significant advances made in the field of infant cognitive development and propose that leveraging insights from this research has the potential to fundamentally shape our understanding of the cognitive architecture of attachment representations in infancy. We also propose that the integration of attachment research into cognitive research can shed light on the role of early experiences, individual differences, and stability and change in infant cognition, as well as open new routes of investigation in cognitive studies, which will further our understanding of human knowledge. We provide recommendations for future research throughout the article and conclude by using our collaborative research as an example.